For example, if you have a logistic regression on certain dataset:
fit <- glm(y ~ x, data = test, family = "binomial")
If you do
predict(fit, newdata, type = "link", se = TRUE), you will get a column named
se.fit, which is the standard error for each predicted y value.
My questions are:
How is the MSE value for the link function is computed here?
The variance of the fitting coefficients are basically the MSE times the variance-covariance matrix, there should be a way to compute the MSE value first. But for response variables that have 0 and 1 values, the link function corresponds to 0 and infinity. In this case, how does the model compute this value? Is there any way I can get the MSE value for the
glmfitting in R?
se.fitthe standard error for the link function value of the fitted line at point
x0, or the standard error for the predicted link function value of